Field of the Invention
The present invention is in the field of enterprise contact center operations, more specifically, optimization of resource usage; information, electronic, and personnel; in enterprise contact centers when routing customer inquiries.
Discussion of the State of the Art
Contact centers have become a necessity for the majority of enterprises. Operating an enterprise contact center efficiently, however continues to be daunting task. For service calls, no matter the amount of training and knowledge base support, agents differ greatly in areas of ability and situational ability. Even when relative proficiencies of agents appear to be known, it is nearly impossible to analyze incoming calls quickly and accurately enough to correctly route the calls using human pre-screeners. This all assumes that the center is populated with the correct “experts” for current customer needs and in the correct proportions. This has led many enterprises to measure call center success and the worth of their agents using metrics such as call queue wait times, mean call turnover times, and adherence to canned procedural documents, none of which really relate to business value. Successful web based service is also extremely difficult to achieve as, for the most part, the customer is left to delve through the available knowledge using keywords that they have generated, which themselves lead to long lists of links that are often ranked by criteria irrelevant to their search. The process often uses significant amounts of time to arrive at the information they desire, if at all. The end result of all of this is mediocre customer satisfaction, or worse, concerning an enterprise's contact center and greatly reduced business value for the entire operation.
The conditions are similar on the sales side. Currently, it is quite difficult to connect a potential customer to the “right” sales person with confidence or, on the web side to quickly get those potential customers to exact information that they need to purchase the enterprises product over that of another. As with service inquiries, the buyer's journey has remained largely reliant on their ingenuity, and possibly a little luck.
More recently, some advancement has been made to improve the union of contact center customers with the information that they require, thereby improving the business value of an enterprise's contact center, through the use of path analytics. In path analytics, the paths taken by a subset of previous customers who have used a specific keyword or small set of keywords on the enterprise's contact center web pages, within contact center emails, or during interaction with the contact center's IVRs are analyzed with some predetermined successful endpoint the goal. These goals may be that the customer purchases a product, the customer responds favorably to a particular marketing campaign, the customer purchases an upgrade to what they originally came for, the customer gives a highly favorable review in a service satisfaction survey. The analyzed paths that go from keywords to achievement of the goal in the least number of “steps” are considered to be the most efficient and future customers who use the same keyword or small set of keywords are henceforth directed down that path. A variant of this path analysis process occurs when a subset of former customers follow a particular path of web page links on an enterprise's web site that ends in a specific, desired goal and that pathway is then codified so that future customers follow it.
While an improvement, path analytics suffers from several shortcomings which make it a weak driver of business value in the contact center sphere. It is passive and retrospective and thus cannot adapt to changing conditions as products mature or are replaced. It relies on a limited number observed states that provide only simplistic deterministic relationships between some data or event within the contact center and an outcome. It relies on a set of decisive endpoints without any glimpse, statistical or otherwise of the customer's decision process or hidden motivation, as a result it cannot give any indication of steps toward optimizing contact center constituency.
What is needed is a system to predictively closely match all contact center related information with customer requests to provide that information in the most efficient and satisfactory manner by routing the customer to the contact center resource, human or electronic with command of the specific knowledge most optimal to both the topic and depth of the customer's request. What is further needed is a system that can accurately and predictively determine the characteristic set needed by prospective contact center resources, both electronic and human, the characteristic set possessed by each of the current call center resources, both electronic and human and their best placement within contact center organization, potentially geographical, to maximize efficiency and business value in the areas of sales and service contract satisfaction.